journal article·2026-04Open access

Ultrafast Multilevel Switching and Synaptic Behavior in a Planar Quantum Topological Memristor

Mamoon Ur Rashid, Usman Safder, Sobia Ali Khan, Anh‐Tuan Pham, Muhammad Sheeraz, Nguyen‐Hoang Dang, Duy Le Thanh, Zeeshan Tahir, Faisal Maqbool, Koo‐Hyun Chung, Sunglae Cho, Jungdae Kim, Yong Soo Kim

Advanced Science· Volume 13· Issue 21

Abstract

ABSTRACT The rapid increase in data driven by analytics and Internet of Things demands innovation in both device architecture and materials to meet the growing need for fast and efficient computing. Here we report an ultrafast planar quantum topological memristor (PQTM), comprised of bismuth‐telluride (Bi 2 Te 3 ) thin film transferred onto pre‐patterned electrodes. Owing to the planar architecture, the device connects both electrodes to the surface states of Bi 2 Te 3, offering a platform to directly benefit from the characteristic features of topological surface states, such as low‐dissipation and scattering‐resistant channels essential for ultrafast‐ and efficient‐charge transport. Pertinently, PQTM presents a forming‐free bipolar‐resistive switching behavior with an ultrafast‐switching ∼15 ± 5 ns and low‐energy consumption ∼14.5 nJ, which is a record high among the topological insulator‐based memristors. Moreover, the endurance evaluation over 10 3 consecutive DC‐switching cycles demonstrates superior stability in both high and low resistive states, while the retention tests display an excellent longevity of ∼10 5 s, signifying reliable non‐volatile operation. Finally, PQTM reproducibility is established via comparison with 24 other devices, presenting multilevel resistive switching exhibiting both digital and analog switching modes together with long‐term potentiation, depression, and persistent image‐recognition performance, corroborated via 1D‐convolutional layers with four LeNet models. Thus, our work emphasizes the critical role of device architecture in harnessing material properties for advanced‐memory and neuromorphic applications.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Topological Materials and Phenomena · Ferroelectric and Negative Capacitance Devices

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Semiconductor Engineering and Energy Harvest‐Storage Research Center University of Ulsan Ulsan South Korea

School of Chemical and Bioprocess Engineering, Engineering and Materials Science Centre University College Dublin (UCD), Belfield Campus Dublin Ireland

New Energy Materials Research Institute Korea Institute of Energy Technology (KENTECH) Naju South Korea

Division of Chemical and Material Metrology Korea Research Institute of Standards and Science (KRISS) Daejeon South Korea

Department of Mechanical Engineering University of Ulsan Ulsan South Korea

Department of Physics and Chemistry Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu South Korea

Funding

National Research Foundation of Korea

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